Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -11,11 +11,11 @@ import gradio as gr
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import spaces
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import torch
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from builder import load_pretrained_model
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from llava.constants import IMAGE_TOKEN_INDEX
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from llava.constants import LOGDIR
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from llava.conversation import (default_conversation, conv_templates)
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from llava.mm_utils import KeywordsStoppingCriteria, tokenizer_image_token
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from llava.utils import (build_logger, violates_moderation, moderation_msg)
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from taxonomy import wrap_taxonomy, default_taxonomy
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@@ -502,7 +502,7 @@ Set the environment variable `model` to change the model:
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'LukasHug/LlavaGuard-13B-hf',
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'LukasHug/LlavaGuard-34B-hf', ]
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bits = int(os.getenv("bits", 16))
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model = os.getenv("model", models[
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available_devices = os.getenv("CUDA_VISIBLE_DEVICES", "0")
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model_path, model_name = model, model.split("/")[0]
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if api_key:
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@@ -516,7 +516,7 @@ Set the environment variable `model` to change the model:
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model_path = '/common-repos/LlavaGuard/models/LlavaGuard-v1.1-7b-full/smid_and_crawled_v2_with_augmented_policies/json-v16/llava'
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print(f"Loading model {model_path}")
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tokenizer, model, image_processor, context_len = load_pretrained_model(model_path, None, model_name
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model.config.tokenizer_model_max_length = 2048 * 2
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exit_status = 0
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import spaces
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import torch
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from llava.constants import IMAGE_TOKEN_INDEX
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from llava.constants import LOGDIR
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from llava.conversation import (default_conversation, conv_templates)
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from llava.mm_utils import KeywordsStoppingCriteria, tokenizer_image_token
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from llava.model.builder import load_pretrained_model
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from llava.utils import (build_logger, violates_moderation, moderation_msg)
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from taxonomy import wrap_taxonomy, default_taxonomy
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'LukasHug/LlavaGuard-13B-hf',
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'LukasHug/LlavaGuard-34B-hf', ]
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bits = int(os.getenv("bits", 16))
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model = os.getenv("model", models[1])
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available_devices = os.getenv("CUDA_VISIBLE_DEVICES", "0")
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model_path, model_name = model, model.split("/")[0]
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if api_key:
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model_path = '/common-repos/LlavaGuard/models/LlavaGuard-v1.1-7b-full/smid_and_crawled_v2_with_augmented_policies/json-v16/llava'
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print(f"Loading model {model_path}")
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tokenizer, model, image_processor, context_len = load_pretrained_model(model_path, None, model_name)
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model.config.tokenizer_model_max_length = 2048 * 2
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exit_status = 0
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